def template_animated_clustering(file, radius, order, expected_cluster_amount):
sample = read_sample(file)
expected_result_obtained = False
analyser = None
while (expected_result_obtained == False):
network = syncnet(sample,
radius,
initial_phases=initial_type.RANDOM_GAUSSIAN,
ccore=True)
analyser = network.process(order, solve_type.FAST, True)
clusters = analyser.allocate_clusters(0.1)
if (len(clusters) == expected_cluster_amount):
print("Expected result is obtained - start rendering...")
expected_result_obtained = True
visualizer = cluster_visualizer()
visualizer.append_clusters(clusters, sample)
visualizer.show()
else:
print(
"Expected result is NOT obtained - rendering is NOT started ( actual:",
len(clusters), ")...")
syncnet_visualizer.animate_cluster_allocation(
sample, analyser, tolerance=0.1, save_movie="clustering_animation.mp4")
def template_animated_clustering(file, radius, order, expected_cluster_amount, title_animation = None):
sample = read_sample(file);
expected_result_obtained = False;
analyser = None;
while (expected_result_obtained == False):
network = syncnet(sample, radius, initial_phases = initial_type.RANDOM_GAUSSIAN, ccore = True);
analyser = network.process(order, solve_type.FAST, True);
clusters = analyser.allocate_clusters(0.1);
if (len(clusters) == expected_cluster_amount):
print("Expected result is obtained - start rendering...")
expected_result_obtained = True;
visualizer = cluster_visualizer();
visualizer.append_clusters(clusters, sample);
visualizer.show();
else:
print("Expected result is NOT obtained - rendering is NOT started ( actual:", len(clusters), ")...");
syncnet_visualizer.animate_cluster_allocation(sample, analyser, tolerance = 0.1, save_movie = "clustering_animation.mp4", title = title_animation);
def testVisualizeClusteringAnimationNoError(self):
sample = read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE1)
network = syncnet(sample, 1.0)
analyser = network.process(0.998, solve_type.FAST, True)
syncnet_visualizer.animate_cluster_allocation(sample, analyser)
def testVisualizerNoFailure(self):
sample = read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE1)
network = syncnet(sample, 1.0, ccore=False)
analyser = network.simulate(25, 5, solve_type.FAST, True)
syncnet_visualizer.animate_cluster_allocation(sample, analyser)
def testVisualizerNoFailure(self):
sample = read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE1);
network = syncnet(sample, 1.0, ccore = False);
analyser = network.simulate(25, 5, solve_type.FAST, True);
syncnet_visualizer.animate_cluster_allocation(sample, analyser);
